暂无分享,去创建一个
[1] Florian Schmidt,et al. BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism , 2018, ArXiv.
[2] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[3] Mathieu Salzmann,et al. Compression-aware Training of Deep Networks , 2017, NIPS.
[4] Hanan Samet,et al. Pruning Filters for Efficient ConvNets , 2016, ICLR.
[5] Wonyong Sung,et al. Structured Pruning of Deep Convolutional Neural Networks , 2015, ACM J. Emerg. Technol. Comput. Syst..
[6] Xiangyu Zhang,et al. ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[7] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[8] Farinaz Koushanfar,et al. Deep3: Leveraging three levels of parallelism for efficient Deep Learning , 2017, 2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC).
[9] Giacomo Indiveri,et al. Deep counter networks for asynchronous event-based processing , 2016, ArXiv.
[10] Song Han,et al. Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding , 2015, ICLR.
[11] Victor S. Lempitsky,et al. Fast ConvNets Using Group-Wise Brain Damage , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Jian Cheng,et al. Quantized Convolutional Neural Networks for Mobile Devices , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Max Welling,et al. Temporally Efficient Deep Learning with Spikes , 2018, ICLR.
[14] Manoj Alwani,et al. Fused-layer CNN accelerators , 2016, 2016 49th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).
[15] Vivienne Sze,et al. Designing Energy-Efficient Convolutional Neural Networks Using Energy-Aware Pruning , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Song Han,et al. Trained Ternary Quantization , 2016, ICLR.
[17] Bo Chen,et al. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications , 2017, ArXiv.
[18] Ran El-Yaniv,et al. Binarized Neural Networks , 2016, ArXiv.
[19] Ran El-Yaniv,et al. Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations , 2016, J. Mach. Learn. Res..
[20] Jungwon Lee,et al. Universal Deep Neural Network Compression , 2018, IEEE Journal of Selected Topics in Signal Processing.
[21] Max Welling,et al. Bayesian Compression for Deep Learning , 2017, NIPS.
[22] Max Welling,et al. Soft Weight-Sharing for Neural Network Compression , 2017, ICLR.
[23] Yoshua Bengio,et al. BinaryConnect: Training Deep Neural Networks with binary weights during propagations , 2015, NIPS.
[24] Bin Liu,et al. Ternary Weight Networks , 2016, ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[25] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[26] Daniel Brand,et al. MEC: Memory-efficient Convolution for Deep Neural Network , 2017, ICML.